A curated archive of frontier intelligence, operator-grade guides, and strategic analysis.
New arXiv research explores multi-agent reinforcement learning (MARL) for safe separation of diverse sUAS fleets in dense urban airspaces, showing PPOA2C policies can achieve equilibrium.
Read the briefing
New arXiv research demonstrates multi-agent reinforcement learning (MARL) can safely deconflict heterogeneous drone fleets in dense urban airspaces, but fairness...
QKVShare enables efficient context transfer between multi-agent LLMs on edge devices using quantized KV-cache handoff, reducing latency and memory overhead.
Agent Island introduces a dynamic, multiagent game environment to benchmark AI agents, designed to resist saturation and contamination, offering a...
New research shows that stronger LLM reasoning can hinder accurate behavioral simulation in multi-agent negotiation, leading to solver-sampler mismatch.
New research reveals homogeneous LLM multi-agent debate often fails due to sycophancy, fragility, and consensus collapse, with self-correction offering better...
Explore the 2026 landscape of AI agent frameworks, comparing provider-native SDKs like OpenAI and Anthropic with independent solutions such as...
Botctl is a new process manager designed to orchestrate autonomous AI agents, addressing deployment, state management, and observability in multi-agent...
Google Scion provides developers with a controlled sandbox to build, debug, and deploy teams of AI agents using Google's latest...
